Abstract

A growing imperative in climate change research is to understand the relative carbon balance of terrestrial ecosystems when they are perturbed by warming and other climate changes. A key limit on potential carbon fixation by deciduous forests is growing season length, a variable know to be sensitive to temperature. Models are a tempting method to untangle species' budburst cues and forecast phenology under warmer climate scenarios. I tested two models' ability to recover parameters used to simulate budburst data. The simpler model was cued only by spring warmth while the complex one modulated warmth requirements with chilling exposure. For the simple model, parameters could be recovered consistently from some, but not all, regions of parameter space. The complex model's parameters were largely unrecoverable. To understand the consequences of parameter uncertainty, I applied both models to an 18 year phenological record of 13 deciduous tree species. While a few species fell into identifiable regions of the simple model's parameter space, most did not, and projected budburst dates had wide parameter-derived uncertainty intervals. These bands were wider still under a 5-degree Celsius warming scenario. Even greater uncertainty resulted from the complex model. These results suggest that attempts to forecast the timing trees' growing seasons, and therefore their potential for carbon fixation in warmer climates, should be treated with caution.